{"id":"W2377074150","doi":"","title":"The comparison of spatial characteristics in urban landuse growth among the central and sub-cities in Shanghai Region","year":2003,"lang":"en","type":"article","venue":"","topic":"Remote Sensing and Land Use","field":"Earth and Planetary Sciences","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"CAE (Canada)","funders":"","keywords":"Urbanization; Geography; Land use; Spatial ecology; Spatial variability; Scale (ratio); Spatial distribution; Common spatial pattern; Physical geography; Spatial heterogeneity; Urban planning; Cartography; Economic geography; Remote sensing; Ecology; Statistics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002133262,0.00006420479,0.0001196776,0.00003019967,0.00007829765,0.00004709816,0.00006502655,0.00003844767,0.00001017596],"category_scores_gemma":[0.0000719401,0.00003105866,0.0000144865,0.00007970115,0.0001013541,0.00004738852,0.000003375428,0.0001101182,0.000001076062],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000001952842,"about_ca_system_score_gemma":0.00001509269,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.02051716,"about_ca_topic_score_gemma":0.1137821,"domain_scores_codex":[0.999327,0.0001335772,0.0001810285,0.00008581749,0.00009228104,0.0001803036],"domain_scores_gemma":[0.9996061,0.0002099747,0.00005605757,0.00008524683,0.00001074854,0.00003185173],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002665253,0.00000630022,0.9930581,0.000004776241,0.000001875821,0.000003998455,0.001033661,0.00001947914,0.000001518791,0.0001229174,0.0001293567,0.005591299],"study_design_scores_gemma":[0.0001689234,0.00003275807,0.9856941,0.00001945732,0.000002635426,0.000003451137,0.0005946386,0.01291673,0.000100896,0.0001165076,0.0003003113,0.00004958741],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9970482,0.0002519348,0.00002191338,0.0001634261,0.0001275943,0.00007552144,0.000002611318,0.000005474483,0.002303308],"genre_scores_gemma":[0.9995893,0.0002289434,0.000009703786,0.00003279944,0.0000305682,5.547856e-8,0.000007823863,0.000001346986,0.00009948533],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09326492,"threshold_uncertainty_score":0.9860053,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01460497606773815,"score_gpt":0.1983804976833308,"score_spread":0.1837755216155927,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}